Senior MLOps Engineer

Overview

As Senior MLOps Engineer at Trainline, you lead the technical direction for ML and AI tooling across the platform. You’ll shape infrastructure and automation for internal ML/AI systems and customer-focused products, delivering reliable, governed deployments. You’ll work with cross-functional teams to raise the bar on platform quality, enable rapid onboarding of new AI initiatives, and mentor others. A meaningful opportunity to influence how Trainline scales ML at pace and maintains security and cost discipline.

Pay / Benefits

• Private healthcare & dental insurance
• Work from abroad policy
• 2-for-1 share purchase plans
• EV Scheme to reduce carbon emissions
• Extra festive time off
• Family-friendly benefits

Responsibilities

• Take a leading technical role to promote ML/AI tooling adoption across teams
• Support AI infrastructure to ensure governance, monitoring, and automated deployment
• Drive a standard deployment approach for ML/AI products to accelerate production onboarding
• Automate service modernization, fix/prevent security vulnerabilities in libraries and dependencies
• Strengthen MLOps foundations with cost tracking, security improvements, and standardized practices
• Contribute to technical strategy and evaluate options with ambiguity
• Communicate decisions clearly and help prioritize ML requests
• Mentor engineers and share knowledge through documentation and enablement across the organization

Key requirements

• IaC and CI/CD tooling proficiency (Terraform, GitHub Actions; CloudFormation/Jenkins are relevant)
• Experience with containerized workloads (Docker) and cloud platforms (AWS preferred, GCP/Azure considered)
• Productionising AI products, including agentic systems and AIOps tooling (AWS Bedrock AgentCore or similar)
• Experience with managed/self-hosted ML infra (e.g., SageMaker, feature stores like Feast, DAG tooling such as Airflow/Metaflow)
• Model experiment tracking (MLflow or Weights & Biases) and monitoring tools (EvidentlyAI, CometML, Grafana, New Relic)
• Production-quality, tested Python code
• Experience leading or contributing to major platform changes and migrations; ability to drive work through ambiguity
• Strong communication, prioritisation, and mentoring track record

• Clear communication
• Strong prioritisation
• Mentoring colleagues
• Terraform
• GitHub Actions
• AWS CloudFormation

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